Technical Field
The present invention relates to an analysis device, an analysis method, and a program.
Background Art
Conventionally, a method for analyzing a system which inputs structured input data including a plurality of input parameters and outputs output data relative to the input data and for specifying, among the input parameters, a parameter which greatly affects output data, has been known (for example, see M. Yamada, et al. High-Dimensional Feature Selection by Feature-Wise Kernelized Lasso. Neural Computation, vol. 26, no. 1, pp. 185-207, 2014).
However, conventionally, it has not been possible to predict the degree of change of output data according to the amount of change of each input parameter of the system, and it has been difficult to estimate suitable input parameters based on prediction results. For example, in a system or problem which sets input data including a large number of input parameters as initial conditions and/or constraints of a model and obtains output data to be evaluated by a complex actual test or simulation, much time and/or a large amount of processing are required to obtain output data of the system.